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Many industrial processes involve particles in a carrier fluid, and it is often of interest to monitor the of these particles noninvasively. The aim of this paper is to develop a theoretical model of multiple particle-wall impact vibrations that can be used to recover the particle size from experimental data. These vibrations have been measured by an ultrasonic transducer attached to the exterior of a vessel containing a stirred-particle-laden fluid. A linear systems model is derived for the response of the piezoelectric ultrasonic transducer, which has a single matching layer. The acceleration power spectrum of these vibrations has been shown experimentally to contain information on the size of the impacting particle. In particular, the frequency of the main spectral lobe is inversely proportional to the particle size. We present a theoretical model that agrees with this empirically observed phenomenon. The theoretical model is then used to simulate multiple particle-wall impacts, with each particle impacting at a randomly chosen location. A set of theoretical vibration spectra arising from multiple particle-wall impacts are integrated and compared with the experimental data. The ability of this approach to distinguish between different particle sizes is clearly shown. [ABSTRACT FROM AUTHOR]

Lovastatin crystals often exhibit an undesirable needle-like morphology. Several studies have shown how a needle-like morphology can be modified in antisolvent crystallisation with the use of additives, but there is much less experimental work demonstrating crystal shape modification without the use of additives. In this study, a series of unseeded continuous antisolvent crystallisation experiments were conducted with the process conditions of supersaturation, total flow rate, and ultrasound level being varied to determine their effects on crystal size and shape. This experimental work involved identifying acetone/water as the most suitable solvent/antisolvent system, assessing lovastatin nucleation behaviour by means of induction time measurements, and then designing and implementing the continuous antisolvent crystallisation experiments. It was found that in order to produce the smallest and least needle-like particles, the maximum total flow rate and supersaturation had to be combined with the application of ultrasound. These results should aid development of pharmaceutical manufacturing processes where the ability to control particle size and shape would allow for optimisation of crystal isolation and more efficient downstream processing. [ABSTRACT FROM AUTHOR]

A digital-first approach to produce quality particles of an active pharmaceutical ingredient across crystallisation, washing and drying is presented, minimising material requirements and experimental burden during development. To demonstrate current predictive modelling capabilities, the production of two particle sizes (D 90 = 42 and 120 µm) via crystallisation was targeted to deliver a predicted, measurable difference in in vitro dissolution performance. A parameterised population balance model considering primary nucleation, secondary nucleation and crystal growth was used to select the modes of production for the different particle size batches. Solubility prediction aided solvent selection steps which also considered manufacturability and safety selection criteria. A wet milling model was parameterised and used to successfully produce a 90 g product batch with a particle size D 90 of 49.3 µm, which was then used as the seeds for cooling crystallisation. A rigorous approach to minimising physical phenomena observed experimentally was implemented, and successfully predicted the required conditions to produce material satisfying the particle size design objective of D 90 of 120 µm in a seeded cooling crystallisation using a 5-stage MSMPR cascade. Product material was isolated using the filtration and washing processes designed, producing 71.2 g of agglomerated product with a primary particle D 90 of 128 µm. Based on experimental observations, the population balance model was reparametrised to increase accuracy by inclusion of an agglomeration term for the continuous cooling crystallisation. The dissolution performance for the two crystallised products is also demonstrated, and after 45 min 104.0 mg of the D 90 of 49.3 µm material had dissolved, compared with 90.5 mg of the agglomerated material with D 90 of 128 µm. Overall, 1513 g of the model compound was used to develop and demonstrate two laboratory scale manufacturing processes with specific particle size targets. This work highlights the challenges associated with a digital-first approach and limitations in current first-principles models are discussed that include dealing ab initio with encrustation, fouling or factors that affect dissolution other than particle size. • Designed a series of unit operations using first-principles mathematical models. • Controlled product performance achieved by modulation of particle size. • Successful digital design of process for particle size D 90 = 49 µm (model: 42 µm). • Separate process for particle size D 90 = 128 µm (model: 120 µm) also accomplished. • Measurable difference in in vitro dissolution performance between particles. [ABSTRACT FROM AUTHOR]

Information about size and shape of particles produced in various manufacturing processes is very important for process and product development because design of downstream processes as well as final product properties strongly depend on these geometrical particle attributes. However, recovery of particle size and shape information in situ during crystallisation processes has been a major challenge. The focused beam reflectance measurement (FBRM) provides the chord length distribution (CLD) of a population of particles in a suspension flowing close to the sensor window. Recovery of size and shape information from the CLD requires a model relating particle size and shape to its CLD as well as solving the corresponding inverse problem. This paper presents a comprehensive algorithm which produces estimates of particle size distribution and particle aspect ratio from measured CLD data. While the algorithm searches for a global best solution to the inverse problem without requiring further a priori information on the range of particle sizes present in the population or aspect ratio of particles, suitable regularisation techniques based on relevant additional information can be implemented as required to obtain physically reasonable size distributions. We used the algorithm to analyse CLD data for samples of needle-like crystalline particles of various lengths using two previously published CLD models for ellipsoids and for thin cylinders to estimate particle size distribution and shape. We found that the thin cylinder model yielded significantly better agreement with experimental data, while estimated particle size distributions and aspect ratios were in good agreement with those obtained from imaging. [ABSTRACT FROM AUTHOR]